 |
| VECTOR | [2-1-0:3] |
|---|---|
| PREVIOUS CODE | MICS 6000D |
| DESCRIPTION | This course is about fundamentals in optics and photonics. The “Optics” part includes ray optics, electromagnetic optics, plasmonics, coherence and polarization of light, etc. The “Photonics” part includes the science behind light generation (e.g. laser), manipulation (e.g. based on nonlinear optics) and photodetection (e.g. PN junction diodes). |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6038) | Tu 01:30PM - 03:20PM | Rm 101, W2 | CHENG, Bojun | 20 | 5 | 15 | 0 | |
| T01 (6039) | Tu 03:30PM - 04:20PM | Rm 101, W2 | CHENG, Bojun | 20 | 5 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | MICS 6000F |
| DESCRIPTION | This course guides the students through the fundamentals of analog integrated circuits design in CMOS technologies. Knowledge in analog design is essential for further research and study in the IC design tracks. This course will cover the operation of MOSFETs, basic concepts of analog circuits design, the implementation of basic analog circuits from MOSFETs, and the realization of more complex CMOS circuits using basic analog building blocks. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6040) | Mo 01:30PM - 04:20PM | Rm 201, W1 | ZONG, Zhirui | 20 | 11 | 9 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | MICS 6000A |
| DESCRIPTION | The course will discuss the application of automated reasoning techniques in the verification of software and hardware components in electronic systems. This course will cover basic knowledge of logic, satisfiability solvers, model checking and their applications. This course also includes topics on circuit testing, for example, automatic test pattern generation and design for testing. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6051) | We 01:30PM - 04:20PM | Rm 201, E4 | ZHANG, Hongce | 20 | 6 | 14 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | MICS 6000I |
| DESCRIPTION | This course introduces the foundations of modern VLSI electronic design automation (EDA), with a focus on optimization and algorithm foundations for VLSI physical design problems. We will introduce partitioning, floor planning, placement, routing, manufacturability optimization, and mask optimization. We will see a set of concrete applications of various conventional optimization techniques in VLSI design, e.g., graph theory, convex programming, numerical optimization, etc. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6041) | Fr 01:30PM - 04:20PM | Rm 202, E1 | MA, Yuzhe | 20 | 7 | 13 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This is a foundation course to clock generation integrated circuit. The topics covered include basic concepts basic oscillator, oscillator analysis, advanced oscillator techniques, basic phase-locked loop architecture, integer-N PLLs, fractional-N PLLs, frequency dividers and multipliers, advanced frequency synthesis and clock data recovery. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6230) | Tu 01:30PM - 04:20PM | Rm 201, W1 | HUANG, Zhiqiang | 20 | 5 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Introduction to the basic semiconductor properties, the basic semiconductor physics, optoelectronic device physics and optoelectronic device applications. It covers general semiconductor properties, crystal structure, crystal growth, energy band, dopants and defects, generation-recombination processes, carrier transport, and PN junction. It also covers optoelectronic efficiencies, light-emitting diodes, photodiodes, solar cells, lasers, MicroLED technologies, LED modulations, and the fabrication of optoelectronic devices. The goal of this course is to develop a comprehensive understanding of the physics and technologies behind the semiconductor and semiconductor optoelectronic devices. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6233) | Tu 09:00AM - 11:50AM | Rm 202, E4 | WANG, Renjie | 20 | 9 | 11 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course is designed to introduce hardware for machine learning to students. It will focus on the basics of deep learning, computations and dataflow of inference and training, hardware accelerator implementations and co-optimization of software and hardware techniques. This course is particularly targeted to help students comprehensively understand the design principles and techniques of hardware accelerators for machine learning systems using state-of-the-art structures (e.g., FPGAs,ASICs, CIM). |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6234) | Fr 01:30PM - 04:20PM | Rm 103, E1 | HUANG, Shanshi | 20 | 10 | 10 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | The functionality and performance of today’s computer system is increasingly dependent on the characteristics of the memory devices. Also, the rapid development of big data, cloud computing and IoT brings new challenges to the design and implementation of memory systems. This course covers the semiconductor memory technologies from the device bit-cell structures to the memory array design with an emphasis on the industry trend and cutting-edge technologies. The topics include discussions of mainstream volatile and nonvolatile memory device technologies (e.g., SRAM, DRAM, FLASH) and their limitations. To go beyond these mature technologies, the course also explores emerging memory device technologies (e.g., STT-MRAM, PCM, RRAM), followed by an introduction of their new applications, including reconfigurable logic, processing-in-memory, deep learning accelerators and neuromorphic hardware. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6235) | Tu 01:30PM - 04:20PM | Rm 202, W1 | JIANG, Hongwu | 20 | 15 | 5 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Parallel processing is ubiquitous in modern computer systems, ranging from smart phones to multicore processors to datacenter computers. This course aims to introduce the fundamental issues and principles in designing modern parallel computers. The course covers parallel programming models and parallel architecture designs, including shared memory, message passing, cache coherence, memory consistency, interconnection network, etc. Classes will be a mixture of lectures and in-class discussions of research papers. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6236) | We 09:00AM - 11:50AM | Rm 201, E4 | HUANG, Jiayi | 20 | 10 | 10 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Being able to customize hardware architecture to application's exact needs, FPGA-based accelerators deliver better efficiency than general architectures such as CPUs. This course provides a comprehensive overview of FPGA-based accelerators and other domian specific architectures from historical contexts to recent trends in system designs spanning a collection of architectural techniques and a variety of application domains. Additionally, the course delves into methods for performance analysis and emphasizes on practical experience with parallel programming for FPGA platforms. This hands-on approach ensures students gain a deep understanding of domain specific architectures. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6237) | Fr 09:00AM - 11:50AM | Rm 201, W4 | CHEN, Xinyu | 20 | 16 | 4 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Switch mode power converters (SMPCs) are the most widely used power management circuits. This course covers the working principles of the SMPCs, along with discussion of the topologies, continuous and discontinuous conduction mode, loop gain analysis and relevant mathematical tools, stability and compensation. This course delves into the design details and optimization of integrated SMPCs. This course provides a comprehensive understanding of the SMPCs. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6238) | Tu 09:00AM - 11:50AM | Rm 201, W4 | CAI, Guigang | 20 | 5 | 15 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Sensors and their associated signal conditioning and processing circuits are the key components in many biomedical instruments which play an important role in the monitoring, diagnosis and treatment of diseases in healthcare. This course provides a comprehensive investigation for some important and widely used sensors and circuits for the biomedical applications with focus on the wearable sensing system and medical imaging system. This course will cover the fundamental working principles of the sensors, the characteristics of the sensing output signals, the signal conditioning and processing circuits, system level integrations, and their biomedical applications. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6239) | We 01:30PM - 04:20PM | Rm 202, E4 | JIANG, Wei | 20 | 8 | 12 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Building on the semiconductor fundamentals and device physics knowledge, this course teaches the latest development and advancement in CMOS devices and emerging device architectures, including novel memory technologies. Major topics to be covered in this course include (i) CMOS transistor scaling physics and short channel effects for nanoscale MOSFETs, (ii) advanced process technologies including high-k gate dielectric, metal gate, ultra-shallow junction, advanced doping techniques, and high mobility channel, (iii) device reliability, high-field behavior, and hot carrier effects, (iv) alternative nanoscale transistor architectures, (v) charge-based memory and non-volatile memory technology, and (vi) more-than-Moore technological trends. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6242) | We 01:30PM - 04:20PM | Rm 201, E3 | LIU, Xiwen | 20 | 9 | 11 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | Random process is everywhere in electrical systems. For example there are noise in circuits, cycle-to-cycle and device-to-device variance and others. All these effects have an impact on system performance. To mitigate or utilize these effects, it is required to capture and characterize these random processes. Probability and statistics is such a powerful tool that is necessary when these random processes are modeled. During the course, the basics of probability and statistics will be addressed. As an example of application, the course will also address how device stochasticity is modeled and leveraged for computing purposes, such as probabilistic computing and Bayesian inference. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6243) | Tu 01:30PM - 04:20PM | Rm 201, E4 | YANG, Kezhou | 20 | 3 | 17 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| DESCRIPTION | This course will provide an introduction to the fundamental principles of microoptics, covering concepts such as coherence, interference, and diffraction. We will also explore the use of microoptics in devices and systems for a range of applications, including telecommunications, computing, imaging, and sensing. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6232) | Mo 01:30PM - 04:20PM | Rm 201, E4 | TONG, Ye Yu | 20 | 8 | 12 | 0 |
| VECTOR | [3-0-0:3] |
|---|---|
| PREVIOUS CODE | SEEN 6000G |
| DESCRIPTION | Spiking Neural Networks represent the third generation of neural network models, differentiating themselves by more closely mimicking the biological processes of the human brain. Unlike traditional artificial neural networks that process information in a continuous manner, SNNs incorporate the concept of time directly into their operating model, using spikes for communication and computation, which makes them powerful tools for modeling temporal dynamics and learning from spatio-temporal data. This course includes modules: Introduction to Neural Computation; Biological Foundations and Neuron Modeling; Network Architectures and Dynamics Connectivity patterns in SNNs; Learning in Spiking Neural Networks, Hebbian learning and STDP; Simulation and lmplementation Tools and frameworks for simulating SNNs; Applications and Future Directions. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6231) | Mo 01:30PM - 04:20PM | Rm 202, W1 | XU, Renjing | 20 | 16 | 4 | 0 |
| VECTOR | [1-3 credit(s)] |
|---|---|
| DESCRIPTION | An independent study on selected topics carried out under the supervision of a faculty member. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6474) | TBA | TBA | TBA | 10 | 1 | 9 | 0 |
| DESCRIPTION | Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6255) | TBA | TBA | TBA | 999 | 18 | 981 | 0 |
| DESCRIPTION | Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| R01 (6256) | TBA | TBA | TBA | 999 | 37 | 962 | 0 |